serverless-modal

# Modal Cloud GPU — Training & Inference Task: $ARGUMENTS ## Overview **Modal** is a serverless GPU cloud. Key advantages over SSH-based platforms (vast.ai, remote servers): - **Zero config**: no SSH, no Docker, no port forwarding. Write Python → `modal run` → done. - **Auto scale-to-zero**: billing stops the instant your code finishes. No idle instances. - **Local-first**: run `modal run` from your laptop. Code, data, and results stay local; only the GPU function runs remotely. - **Reproducible environments**: dependencies declared in code via `modal.Image`, not system-level packages. **Best for**: Users without a local GPU who need to debug CUDA code, run small-scale tests, or iterate quickly on experiments. The $5 free tier (no card) is enough for code debugging; $30 (with card) covers most small-scale experiment runs. **Trade-off**: Modal costs more per GPU-hour than vast.ai or Lightning for some GPU tiers, but eliminates setup time and idle billing, often making it cheaper for short/medium workloads. For long training runs (>4 hours), consider vast.ai for lower $/hr. ## Authentication ```bash pip install modal modal setup # Opens browser login, writes token to ~/.modal.toml # Verify: modal run -q 'print("ok")' ``` - Sign up: https://modal.com (GitHub/Google login) - Free (no card): **$5/month** — enough for quick tests - Free (with card): **$30/month** — bind a payment method at https://modal.com/settings for the full free tier. Set a **workspace spendin...